New data-driven mathematical models of collective cell motion

集体细胞运动的新数据驱动数学模型

• 批准号: FT130100148
• 负责人: Prof Matthew Simpson
• 金额: $ 43.08万
• 依托单位: Queensland University of Technology
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-06-30 至 2018-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT130100148
• 关键词: New; data; driven; mathematical; models

Cancer and chronic wounds are a national, and indeed, international health problem set to worsen as our population ages. Predictive and interpretive tools are required to improve our understanding of collective cell migration in relation to cancer and chronic wounds. This project will produce new validated mathematical tools for predicting collective cell migration in a general framework that can deal with application-specific details, such as the role of cell shape and cell size. Although cell shape and size are known to affect collective cell migration, standard mathematical models ignore these details. This project will produce new predictive mathematical modelling tools that are validated by new experimental data.

癌症和慢性伤口是国际健康问题，随着我们的人口年龄的增长，国际健康问题将恶化。需要预测性和解释性工具来提高我们对癌症和慢性伤口相关的集体细胞迁移的理解。该项目将产生新的经过验证的数学工具，用于在一般框架中预测集体细胞迁移，该框架可以处理特定于应用程序的细节，例如细胞形状和细胞大小的作用。尽管已知细胞形状和大小会影响集体细胞迁移，但标准数学模型忽略了这些细节。该项目将生成新的预测数学建模工具，这些工具已通过新的实验数据验证。